app.py

# app.py

import gradio as gr
import torch
from PIL import Image
from model import load_model
from utils import preprocess_image, decode_predictions
import os

# Load the model (ensure the path is correct)
MODEL_PATH = "saved_models/finetuned/finetuned_recog_model.pth"
FONT_PATH = "fonts/NotoSansEthiopic-Regular.ttf"  # Update the path to your font

# Check if model file exists
if not os.path.exists(MODEL_PATH):
    raise FileNotFoundError(f"Model file not found at {MODEL_PATH}. Please provide the correct path.")

# Check if font file exists
if not os.path.exists(FONT_PATH):
    raise FileNotFoundError(f"Font file not found at {FONT_PATH}. Please provide the correct path.")

# Load the model
device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
model = load_model(MODEL_PATH, device=device)

# Load the font for rendering Amharic text
from matplotlib import font_manager as fm
import matplotlib.pyplot as plt

ethiopic_font = fm.FontProperties(fname=FONT_PATH, size=15)

def recognize_text(image: Image.Image):
    """
    Function to recognize text from an image.
    """
    # Preprocess the image
    input_tensor = preprocess_image(image).unsqueeze(0).to(device)  # [1, 3, 224, 224]
    
    # Perform inference
    with torch.no_grad():
        log_probs = model(input_tensor)  # [H*W, 1, vocab_size]
    
    # Decode predictions
    recognized_texts = decode_predictions(log_probs)
    
    return recognized_texts[0]

def display_image_with_text(image: Image.Image, recognized_text: str):
    """
    Function to display the image with recognized text.
    """
    plt.figure(figsize=(6,6))
    plt.imshow(image)
    plt.axis('off')
    plt.title(f"Recognized Text: {recognized_text}", fontproperties=ethiopic_font)
    plt.show()
    return plt

# Define Gradio Interface
iface = gr.Interface(
    fn=recognize_text,
    inputs=gr.inputs.Image(type="pil"),
    outputs=gr.outputs.Textbox(),
    title="Amharic Text Recognition",
    description="Upload an image containing Amharic text, and the model will recognize and display the text."
)

# Launch the Gradio app
if __name__ == "__main__":
    iface.launch()